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Accuracy Assessment (accuracy + assessment)
Selected AbstractsAccuracy assessment of the MODIS snow products,HYDROLOGICAL PROCESSES, Issue 12 2007Dorothy K. Hall Abstract A suite of Moderate-Resolution Imaging Spectroradiometer (MODIS) snow products at various spatial and temporal resolutions from the Terra satellite has been available since February 2000. Standard products include daily and 8-day composite 500 m resolution swath and tile products (which include fractional snow cover (FSC) and snow albedo), and 0·05° resolution products on a climate-modelling grid (CMG) (which also include FSC). These snow products (from Collection 4 (C4) reprocessing) are mature and most have been validated to varying degrees and are available to order through the National Snow and Ice Data Center. The overall absolute accuracy of the well-studied 500 m resolution swath (MOD10_L2) and daily tile (MOD10A1) products is ,93%, but varies by land-cover type and snow condition. The most frequent errors are due to snow/cloud discrimination problems, however, improvements in the MODIS cloud mask, an input product, have occurred in ,Collection 5' reprocessing. Detection of very thin snow (<1 cm thick) can also be problematic. Validation of MOD10_L2 and MOD10A1 applies to all higher-level products because all the higher-level products are all created from these products. The composited products may have larger errors due, in part, to errors propagated from daily products. Recently, new products have been developed. A fractional snow cover algorithm for the 500 m resolution products was developed, and is part of the C5 daily swath and tile products; a monthly CMG snow product at 0·05° resolution and a daily 0·25° resolution CMG snow product are also now available. Similar, but not identical products are also produced from the MODIS on the Aqua satellite, launched in May 2002, but the accuracy of those products has not yet been assessed in detail. Published in 2007 by John Wiley & Sons, Ltd. [source] Accuracy assessment of computer-assisted flapless implant placement in partial edentulismJOURNAL OF CLINICAL PERIODONTOLOGY, Issue 4 2010N. Van Assche Van Assche N, van Steenberghe D, Quirynen M, Jacobs R. Accuracy assessment of computer-assisted flapless implant placement in partial edentulism. J Clin Periodontol 2010; 37: 398,403. doi: 10.1111/j.1600-051X.2010.01535.x Abstract Aim: To assess the accuracy of implants placed flapless by a stereolithographic template in partially edentulous patients. Material and Methods: Eight patients, requiring two to four implants (maxilla or mandible), were consecutively recruited. Radiographical data were obtained by means of a cone beam or a multi-slice CT scan and imported in a software program. Implants (n=21) were planned in a virtual environment, leading to the manufacture of one stereolithographic template per patient to guide the implant placement in a one-stage flapless procedure. A postoperative cone beam CT was performed to calculate the difference between virtual implant (n=21) positions in the preoperative planning and postoperative situation. Results: A mean angular deviation of 2.7° (range 0.4,8, SD 1.9), with a mean deviation at the apex of 1.0 mm (range 0.2,3.0, SD 0.7), was observed. If one patient, a dropout because of non-conformity with the protocol, was excluded, the angular deviation was reduced to 2.2° (range 0.6,3.9, SD 1.1), and the apical deviation to 0.9 mm (range 0.2,1.8). Conclusion: Based on this limited patient population, a flapless implant installation appears to be a useful procedure even when based on accurate and reliable 3D CT-based image data and a dedicated implant planning software. [source] Optical remote mapping of rivers at sub-meter resolutions and watershed extentsEARTH SURFACE PROCESSES AND LANDFORMS, Issue 1 2008W. Andrew Marcus Abstract At watershed extents, our understanding of river form, process and function is largely based on locally intensive mapping of river reaches, or on spatially extensive but low density data scattered throughout a watershed (e.g. cross sections). The net effect has been to characterize streams as discontinuous systems. Recent advances in optical remote sensing of rivers indicate that it should now be possible to generate accurate and continuous maps of in-stream habitats, depths, algae, wood, stream power and other features at sub-meter resolutions across entire watersheds so long as the water is clear and the aerial view is unobstructed. Such maps would transform river science and management by providing improved data, better models and explanation, and enhanced applications. Obstacles to achieving this vision include variations in optics associated with shadows, water clarity, variable substrates and target,sun angle geometry. Logistical obstacles are primarily due to the reliance of existing ground validation procedures on time-of-flight field measurements, which are impossible to accomplish at watershed extents, particularly in large and difficult to access river basins. Philosophical issues must also be addressed that relate to the expectations around accuracy assessment, the need for and utility of physically based models to evaluate remote sensing results and the ethics of revealing information about river resources at fine spatial resolutions. Despite these obstacles and issues, catchment extent remote river mapping is now feasible, as is demonstrated by a proof-of-concept example for the Nueces River, Texas, and examples of how different image types (radar, lidar, thermal) could be merged with optical imagery. The greatest obstacle to development and implementation of more remote sensing, catchment scale ,river observatories' is the absence of broadly based funding initiatives to support collaborative research by multiple investigators in different river settings. Copyright © 2007 John Wiley & Sons, Ltd. [source] ModEco: an integrated software package for ecological niche modelingECOGRAPHY, Issue 4 2010Qinghua Guo ModEco is a software package for ecological niche modeling. It integrates a range of niche modeling methods within a geographical information system. ModEco provides a user friendly platform that enables users to explore, analyze, and model species distribution data with relative ease. ModEco has several unique features: 1) it deals with different types of ecological observation data, such as presence and absence data, presence-only data, and abundance data; 2) it provides a range of models when dealing with presence-only data, such as presence-only models, pseudo-absence models, background vs presence data models, and ensemble models; and 3) it includes relatively comprehensive tools for data visualization, feature selection, and accuracy assessment. [source] Investigating Global and Local Categorical Map Configuration Comparisons Based on Coincidence MatricesGEOGRAPHICAL ANALYSIS, Issue 2 2009T. K. Remmel The simple and intuitive nature of the coincidence matrix has not only made it the current "gold standard" for accuracy assessment (based on a sample of map pixels), but also a common tool for describing difference between two categorical maps (when all pixels are enumerated). It is this latter case of map comparison that this article explores. Coincidence matrices, although providing significant information regarding thematic agreement between two categorical maps (composition), can lack significantly in terms of conveying information about differences or similarities in the spatial arrangement (configuration) of those map categories in geographic space. This article introduces means for distilling the available configuration information from a coincidence matrix while demonstrating some simple categorical map comparisons. Specifically, while the coincidence matrix summarizes per-pixel compositional persistence or change, the introduced technique further quantifies the global and local configurational uncertainty between compared maps. I demonstrate how this quantification of configurational uncertainty can be used to gauge which thematic mismatch types are most significant and how to measure/present local configurational uncertainty in a spatial context. Implementation is through a straightforward mathematical algorithm in R that is illustrated by several examples. La sencillez y características las matrices de confusión (tablas de contingencia o de error) no sólo la ha convertido en (1) el estándar por excelencia para la evaluación de confiabilidad (veracidad o validez) de mapas temáticos en escala nominal (en base de una muestra de pixeles en un mapa), sino también en (2) una herramienta común para describir la diferencia entre dichos mapas (cuando todos los pixeles son tomados en cuenta). Este segundo uso de las matrices de confusión es el tema explorado por el presente artículo. A pesar de proporcionar información importante acerca de la confiabilidad temática entre dos mapas de categorías nominales (composición), las matrices de confusión sufren de limitaciones importantes cuando el objetivo es extraer información acerca del patrón o arreglo espacial (configuración) de las categorías del mapa. El presente artículo presenta herramientas para destilar la información de configuración espacial disponible a partir de una matriz de confusión, y al mismo tiempo, ilustra algunas comparaciones entre mapas de categorías nominales. En términos más concretos, la matriz de confusión resume la persistencia o cambio en la composición a nivel de cada pixel. La nueva técnica presentada en este estudio incluye además la cuantificación de la incertidumbre en la configuración de los mapas comparados. El autor demuestra cómo esta cuantificación puede ser utilizada para darse una idea de cuáles tipos de errores temáticos son más importantes, y cómo se puede medir e ilustrar la incertidumbre de la configuración local en el contexto espacial. La implementación del método se realiza a través de un algoritmo matemático sencillo en lenguaje R, el mismo que es ilustrado con varios ejemplos. [source] Measuring the Accuracy of Facial Approximations: A Comparative Study of Resemblance Rating and Face Array MethodsJOURNAL OF FORENSIC SCIENCES, Issue 1 2008Carl N. Stephan Ph.D. Abstract:, The success of facial approximation is thought to depend, at least in part, upon the "accuracy" of the constructed face. However, methods of accuracy assessment are varied and this range in methods may be responsible for the disparate results reported in the literature. The aim of this study was to determine if the accuracy results of one facial approximation were comparable across two different assessment methods (resemblance ratings and simultaneous face array tests using unfamiliar assessors) and if resemblance ratings co-varied with recognition responses. True-positive recognition performance from the facial approximation was poor (21%) while resemblance scores using the same facial approximation were moderately high (3 out of 5 on a five-point scale). These results are not, therefore, consistent and indicate that either different variables are being evaluated by the methods, or the same variable is being examined but with different weight/calibration. Further resemblance ratings tests of the facial approximation to three foil faces from the face array revealed that resemblance scores were similar irrespective of which face was compared, and did not closely correspond with the degree of recognition performance. This was especially the case for isolated comparisons of single faces to the facial approximation. Collectively, these results indicate that resemblance ratings are: (i) insensitive measures of a facial approximation's accuracy; and (ii) inconsistent with results of unfamiliar simultaneous face-array recognition results. These data suggest that familiar and unfamiliar recognition tests should be given increased weight in contrast to current resemblance rating tests. [source] Evaluation of Information Loss in Digital Elevation Models With Digital Photogrammetric SystemsTHE PHOTOGRAMMETRIC RECORD, Issue 95 2000Y. D. Huang Information loss is caused when a surface is sampled with a finite interval, such as in the production of a digital elevation model (DEM). This information loss can become the dominant part of the error in a DEM. The ability to quantify information loss enables guidance to be provided for an appropriate choice of grid interval and better accuracy assessment for the DEM. With the use of digital photogrammetric systems, evaluation of information loss has become much easier. This paper describes three methods of evaluating information loss. An example is given of the method which is most appropriate for use with a digital photogrammetric system, based on rock cliff surface data and the VirtuoZo system. [source] Application of QuickBird and aerial imagery to detect Pinus radiata in remnant vegetationAUSTRAL ECOLOGY, Issue 6 2010NERISSA HABY Abstract The invasion of Pinus radiata from long-term established plantations is contributing to the degradation of fragmented and isolated remnants of native vegetation. Within the south-east of South Australia, the 20 vegetation communities that occur within 500 m of a plantation edge are at risk, including nine state threatened communities. To plan effective mitigation strategies, the current extent and distribution of P. radiata needs to be ascertained. High spatial resolution, multispectral QuickBird imagery and aerial photography were used to classify P. radiata within eucalypt and acacia woodlands, melaleuca shrubland, modified pasture and an Eucalyptus globulus plantation. Unsupervised classification of aerial photography gave the best result showing reasonable conformity with the observed distribution of P. radiata at the site scale. However, the 9.4 ± 13.5 (SD) cover classified in the quadrats sampled for the accuracy assessment exceeded the 1.4 ± 2.4 (SD) P. radiata cover determined from an independent dataset. Only 30.1 ± 37.9% (SD) of trees within the quadrats and 9.40 ± 13.49% (SD) of their foliage cover were classified. Trees detected by partial classification of canopy were positively correlated with both tree height and canopy diameter. Overall, the low detection rates were attributed to insufficient spectral resolution. Using higher resolution imagery, together with an object-based image analysis or combination of multispectral and airborne digital image classification, restricted to large emergent adult trees using LiDAR analysis, is likely to improve adult P. radiata detection accuracy. [source] | |||||||||||||